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Intelligent Data Engineering and Automated Learning – IDEAL 2023

24th International Conference, Évora, Portugal, November 22–24, 2023, Proceedings

  • Conference proceedings
  • © 2023

Overview

Editors:
  1. Paulo Quaresma

    1. University of Évora, Évora, Portugal

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  2. David Camacho

    1. Technical University of Madrid, Madrid, Spain

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  3. Hujun Yin

    1. University of Manchester, Manchester, UK

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  4. Teresa Gonçalves

    1. University of Évora, Évora, Portugal

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  5. Vicente Julian

    1. Polytechnic University of Valencia, Valencia, Spain

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  6. Antonio J. Tallón-Ballesteros

    1. University of Huelva, Huelva, Spain

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 14404)

Included in the following conference series:

Conference proceedings info: IDEAL 2023.

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Table of contents (49 papers)

  1. Front Matter

    Pages i-xvii
    Download chapter PDF

  2. Main Track

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Optimization of Image Acquisition for Earth Observation Satellites via Quantum Computing

      • Antón Makarov, Márcio M. Taddei, Eneko Osaba, Giacomo Franceschetto, Esther Villar-Rodríguez, Izaskun Oregi
      Pages 3-14

    3. Complexity-Driven Sampling for Bagging

      • Carmen Lancho, Marcilio C. P. de Souto, Ana C. Lorena, Isaac Martín de Diego
      Pages 15-21

    4. A Pseudo-Label Guided Hybrid Approach for Unsupervised Domain Adaptation

      • Eva Blanco-Mallo, Verónica Bolón-Canedo, Beatriz Remeseiro
      Pages 22-27

    5. Combining of Markov Random Field and Convolutional Neural Networks for Hyper/Multispectral Image Classification

      • Halil Mertkan Sahin, Bruce Grieve, Hujun Yin
      Pages 28-38

    6. Plant Disease Detection and Classification Using a Deep Learning-Based Framework

      • Mridul Ghosh, Asifuzzaman Lasker, Poushali Banerjee, Anindita Manna, Sk Md Obaidullah, Teresa Gonçalves et al.
      Pages 39-50

    7. Evaluating Text Classification in the Legal Domain Using BERT Embeddings

      • José Alfredo F. Costa, Nielsen Castelo D. Dantas, Esdras Daniel S. A. Silva
      Pages 51-63

    8. Rapid and Low-Cost Evaluation of Multi-fidelity Scheduling Algorithms for Hyperparameter Optimization

      • Aakash Mishra, Jeremy Hsu, Frank D’Agostino, Utku Sirin, Stratos Idreos
      Pages 64-69

    9. The Applicability of Federated Learning to Official Statistics

      • Joshua Stock, Oliver Hauke, Julius Weißmann, Hannes Federrath
      Pages 70-81

    10. Generating Wildfire Heat Maps with Twitter and BERT

      • João Cabral Pinto, Hugo Gonçalo Oliveira, Alberto Cardoso, Catarina Silva
      Pages 82-94

    11. An Urban Simulator Integrated with a Genetic Algorithm for Efficient Traffic Light Coordination

      • Carlos H. Cubillas, Mariano M. Banquiero, Juan M. Alberola, Victor Sánchez-Anguix, Vicente Julián, Vicent Botti
      Pages 95-106

    12. GPU-Based Acceleration of the Rao Optimization Algorithms: Application to the Solution of Large Systems of Nonlinear Equations

      • Bruno Silva, Luiz Guerreiro Lopes
      Pages 107-119

    13. Direct Determination of Operational Value-at-Risk Using Descriptive Statistics

      • Peter Mitic
      Pages 120-129

    14. Using Deep Learning Models to Predict the Electrical Conductivity of the Influent in a Wastewater Treatment Plant

      • João Pereira, Pedro Oliveira, M. Salomé Duarte, Gilberto Martins, Paulo Novais
      Pages 130-141

    15. Unsupervised Defect Detection for Infrastructure Inspection

      • N. P. García-de-la-Puente, Rocío del Amor, Fernando García-Torres, Adrián Colomer, Valery Naranjo
      Pages 142-153

    16. Generating Adversarial Examples Using LAD

      • Sneha Chauhan, Loreen Mahmoud, Tanay Sheth, Sugata Gangopadhyay, Aditi Kar Gangopadhyay
      Pages 154-165

    17. Emotion Extraction from Likert-Scale Questionnaires

      • Renata Magalhães, Francisco S. Marcondes, Dalila Durães, Paulo Novais
      Pages 166-176

    18. Recent Applications of Pre-aggregation Functions

      • G. Lucca, C. Marco-Detchart, G. Dimuro, J. A. Rincon, V. Julian
      Pages 177-185

    19. A Probabilistic Approach: Querying Web Resources in the Presence of Uncertainty

      • Asma Omri, Djamal Bensliamne, Mohamed Nazih Omri
      Pages 186-195
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  1. Intelligent Data Engineering and Automated Learning – IDEAL 2023

Keywords

About this book

This book constitutes the proceedings of the 24th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2023, held in Évora, Portugal, during November 22–24, 2023.


The 45 full papers and 4 short papers presented in this book were carefully reviewed and selected from 77 submissions. IDEAL 2023 is focusing on big data challenges, machine learning, deep learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspired models, agents and hybrid intelligent systems, and real-world applications of intelligence techniques and AI.


The papers are organized in the following topical sections: main track; special session on federated learning and (pre) aggregation in machine learning; special session on intelligent techniques for real-world applications of renewable energy and green transport; and special session on data selection in machine learning.

Editors and Affiliations

  • University of Évora, Évora, Portugal

    Paulo Quaresma, Teresa Gonçalves

  • Technical University of Madrid, Madrid, Spain

    David Camacho

  • University of Manchester, Manchester, UK

    Hujun Yin

  • Polytechnic University of Valencia, Valencia, Spain

    Vicente Julian

  • University of Huelva, Huelva, Spain

    Antonio J. Tallón-Ballesteros

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